Direct observation of aqueous secondary organic aerosol from biomass-burning emissions Stefania Gilardonia,1, Paola Massolib, Marco Paglionea, Lara Giulianellia, Claudio Carbonea,2, Matteo Rinaldia, Stefano Decesaria, Silvia Sandrinia, Francesca Costabilec, Gian Paolo Gobbic, Maria Chiara Pietrogranded, Marco Visentind, Fabiana Scottoe, Sandro Fuzzia, and Maria Cristina Facchinia a Italian National Research Council–Institute of Atmospheric Sciences and Climate, 40129 Bologna, Italy; bAerodyne Research Inc., Billerica, MA 01821; cItalian National Research Council–Institute of Atmospheric Sciences and Climate, 00133 Rome, Italy; dDepartment of Chemical and Pharmaceutical Sciences, University of Ferrara, 44121 Ferrara, Italy; and eAgenzia Regionale per la Prevenzione, l’Ambiente e L’Energia, 40139 Bologna, Italy
Edited by Barbara J. Finlayson-Pitts, University of California, Irvine, CA, and approved July 11, 2016 (received for review February 9, 2016)
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particulate matter air quality secondary organic aerosol biomass burning aqueous processing
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rganic aerosol (OA) is a dominant component of atmospheric aerosol. Field observations indicate that processed, that is, secondary OA (SOA), dominates over primary OA worldwide (1–3). Bottom-up and top-down estimates confirm that SOA accounts for up to 76% of ambient OA (1, 4). However, the estimates of global SOA budget are still largely uncertain (1, 5). An increasing number of experimental and modeling studies point toward aqueous-phase chemistry as a significant missing pathway for SOA formation (6–8). To date, most studies have investigated the formation of aqueous SOA (aqSOA) from natural biogenic emissions (6–8). Nevertheless, anthropogenic emissions, such as wood burning for residential heating, can contribute to the formation of aqSOA, both in urban and rural areas. In fact, water-soluble organic species (WSOC) can account for more than 50% of wood-burning emissions (9–11). Monosaccharides, dicarboxylic acids, and phenols emitted during wood combustion can act as aqSOA precursors (12–15). A few studies investigated formation and properties of aqSOA from biomass combustion through laboratory photochemical oxidation of single compounds, such as levoglucosan and phenolic species (12, 13, 16–18). However, ambient observations of aqSOA formation in environments with high wood-burning emissions are very limited. Phenol oligomers, which are tracers of primary wood burning and aqueous-phase processing of wood-burning emissions, were observed in Fresno in Winter 2006, but concentration and properties of the related aqSOA were not reported (16). The influence of aqueous-phase chemistry for SOA formation was suggested again in Fresno in Winter 2010 (19), but the oxidation level [oxygen-to-carbon ratio (O:C)] of the Fresno SOA was lower than expected, compared with the O:C of aqSOA formed from oxidation of wood-burning emissions in laboratory experiments (12–14, 16, 20). www.pnas.org/cgi/doi/10.1073/pnas.1602212113
To identify, quantify, and characterize aqSOA from biomass burning under real ambient conditions, we investigated the OA properties of ambient aerosol and fog water samples collected in the Po Valley (northern Italy) during the cold season, when the region is characterized by temperature below 10 °C, high relative humidity, and significant emissions from wood combustion from residential heating (21). We showed the usefulness of molecular tracer detection by on-line measurement techniques to track the formation of ambient aqSOA. We also infer that oxidation of biomass-burning emissions in wet aerosol is taking place mainly through the formation of hydroxyl/ether groups and oligomerization reactions. Finally, we show that aqSOA originating from biomass-burning emissions are strong absorbers of UV and visible light, thereby contributing to a positive direct forcing. Discussion Ambient Observations of SOA Formed in the Aqueous Phase. The
observations discussed here were obtained during two different field experiments. The first study was performed at the rural site of San Pietro Capofiume (SPC), near Bologna, in Fall 2011, whereas the second experiment took place at an urban background site in Bologna during Winter 2013. The Fall 2011 campaign at SPC (SPC2011) was characterized by several fog episodes. The evaporation of fog left behind particles enriched in oxidized OA. To study the specific effect of fog dissipation on OA properties, we focused on four dissipation Significance Organic aerosol (OA) is a dominant component of atmospheric aerosol worldwide, and it is recognized as a key factor affecting air quality and possibly climate. Observations indicate that more than one-half of the global OA is of secondary origin. Traditional models typically underpredict secondary organic aerosol (SOA) mass, suggesting that a complete knowledge of SOA formation mechanisms is lacking. We show that aqueous-phase processing of biomass-burning emissions contributes to SOA formation. Such aqueous SOA absorbs UV and visible light more efficiently that other OA components. Aqueous chemistry processing of biomass-burning emissions should be taken into account in air quality and climate models for a correct description of the global OA budget and its climate-relevant optical properties. Author contributions: S.G., S.F., and M.C.F. designed research; S.G., M.P., L.G., C.C., M.R., S.D., S.S., M.C.P., M.V., and F.S. performed research; S.G., P.M., M.P., F.C., and G.P.G. analyzed data; and S.G., P.M., and M.P. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. Freely available online through the PNAS open access option. 1
To whom correspondence should be addressed. Email: [email protected].
2
Present address: Proambiente S.c.r.l., CNR Research Area, 40129 Bologna, Italy.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.1602212113/-/DCSupplemental.
PNAS | September 6, 2016 | vol. 113 | no. 36 | 10013–10018
EARTH, ATMOSPHERIC, AND PLANETARY SCIENCES
The mechanisms leading to the formation of secondary organic aerosol (SOA) are an important subject of ongoing research for both air quality and climate. Recent laboratory experiments suggest that reactions taking place in the atmospheric liquid phase represent a potentially significant source of SOA mass. Here, we report direct ambient observations of SOA mass formation from processing of biomass-burning emissions in the aqueous phase. Aqueous SOA (aqSOA) formation is observed both in fog water and in wet aerosol. The aqSOA from biomass burning contributes to the “brown” carbon (BrC) budget and exhibits light absorption wavelength dependence close to the upper bound of the values observed in laboratory experiments for fresh and processed biomass-burning emissions. We estimate that the aqSOA from residential wood combustion can account for up to 0.1–0.5 Tg of organic aerosol (OA) per y in Europe, equivalent to 4–20% of the total OA emissions. Our findings highlight the importance of aqSOA from anthropogenic emissions on air quality and climate.
10014 | www.pnas.org/cgi/doi/10.1073/pnas.1602212113
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events that were not perturbed by transport of air masses from surrounding areas (Supporting Information, 1. Identification of Radiative Fog Dissipation Events at San Pietro Capofiume During the 2011 Study and Table S1). The OA was analyzed by the Aerodyne (Aerodyne Research) high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) (22). The campaign results have been reported in a previous work (23). In this study, the SOA mass spectrum for each fog event is obtained as the total OA minus the primary OA, as determined by positive matrix factorization (PMF) analysis; the spectrum of fog water samples is instead measured via off-line analysis (see Methods for details). The SOA spectra after fog dissipation are very similar to the OA spectrum in fog water (Fig. S1), with a Pearson correlation coefficient (r) larger than 0.96 in all cases (and P < 0.001). This result indicates that the OA species observed in the aerosol particle phase after fog dissipation were originally present in fog water. The field experiment performed in Bologna in Winter 2013 (Bologna2013) was characterized by temperatures below 10 °C, high relative humidity, and stagnant air. Although dense fog events did not occur in the urban setting, the ambient relative humidity was typically above 70%, favoring the presence of wet aerosol particles. Similar to SPC2011, we applied PMF analysis (24) on the HR-ToF-AMS data collected in Bologna2013, to deconvolve the total OA signal in various components (Supporting Information, 4. Positive Matrix Factorization Analysis, 4.1. Positive Matrix Factorization of HR-TOF-AMS OA Data During Bologna 2013). Among the different OA types, we identified an oxygenated organic aerosol (OOA) component originating from biomass burning that has mass spectral features similar to the SOA observed in SPC2011 after fog dissipation (correlation with r = 0.94 and P < 0.001), therefore suggesting influence of aqueous-phase processing. From now on, we refer to these SOAs as aqSOAs. The spectra of the aqSOA for SPC2011 and Bologna2013 are shown together in Fig. 1A, and they show characteristic signals at m/z 29 (CHO+), m/z 43 (C2H3O+), m/z 44 (CO2+), and m/z 60 (C2H4O2+). In the following paragraphs, we report a series of findings to support our hypothesis that these SOAs are indeed aqSOAs. The first evidence of aqSOA formation is given by the correlation of these SOA samples with a tracer of liquid phase chemistry, that is, the hydroxymethanesulfonate (HMS). HMS is formed from the complexation of sulfite and bisulfite with aqueous formaldehyde (25–28). During both campaigns, HMS was detected by the HR-ToF-AMS and was also measured by proton NMR (H-NMR) (Methods and Supporting Information, 2. Tracers of Aqueous-Phase Chemistry and Fig. S2). For SPC2011, the aqSOA concentration increased together with the HMS signal after fog dissipation (r = 0.77, P < 0.001). Because photochemistry prevents HMS formation, the correlation of HMS with aqSOA could not be justified by radiation increase during the first hours after sunrise, when fog dissipates. Instead, the data indicate that HMS and aqSOA were formed in the same environment, that is, in the aqueous phase, consistent with previous literature (8, 29). Good correlation (r = 0.68, P < 0.001) is found between aqSOA and HMS signal for Bologna2013 as well. In addition, Fig. 1B shows that aqSOA in Bologna correlates well (r = 0.73, P < 0.001) with the aerosol liquid water content (ALWC) estimated from particle composition (Methods), confirming that the aqueous phase was the formation medium for this OA. Second, we consider the elemental composition of the aqSOA (Table 1). The O:C ratios observed for the aqSOA in this study are around 0.61–0.62 as calculated with the Aiken ambient (AA) method (Table 1). The corresponding ambient improved (AI) O:C ratios (0.81–0.84) are similar to the AI O:C ratio of aqSOA obtained from laboratory oxidation of phenolic compounds (13, 16). Enhanced O:C ratios (AA O:C > 0.52) have also been reported for laboratory-generated SOA from the photooxidation of organic precursors in the aqueous phase (14, 20). Moreover, higher-than-usual O:C of SOA observed in various environments
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Fig. 1. Evidence of aqSOA formation. (A) Comparison of aqSOA mass spectra in Bologna2013 and in SPC2011; the spectra are highly correlated (r = 94, P < 0.001). Notably, the mass spectrum of the SPC2011 aqSOA has a much larger CO2+ fraction than the spectrum of Bologna2013 aqSOA. (B) Scatter plot of aqSOA vs. the estimated aerosol liquid water content (ALWC) for Bologna2013 (upper and lower bounds). (C) Normalized size distribution of mass fragment m/z 60 (Org60) in BBOA-rich particles (i.e., samples with BBOA organic mass fraction larger than 70%) and in aqSOA-rich particles (i.e., samples with aqSOA organic mass fraction larger than 30%, and corrected for BBOA contribution).
at high relative humidity have been correctly modeled and explained solely by an aqueous-phase chemistry scheme (7). Last, we consider the particle size distribution of the aqSOA. Fig. 1C shows the size distribution of the mass fragment at m/z 60 (C2H4O2+; exact mass, 60.0206), or Org60, a marker for biomass burning (30) and a component of aqSOA mass spectrum. During the Bologna2013 campaign (Fig. 1C, Left), the size distribution of Org60 for the aqSOA factor shows a median mass diameter above 700-nm Dva, consistently with aqueous-phase reaction products (31). Additional particle time-of-flight (pToF) size distributions for other aerosol species during Bologna2013 are reported in Fig. S3. For SPC2011 (Fig. 1C, Right), the pToF size distributions of organic and inorganic chemical species are analyzed in a previous work (23). They are characterized by smaller mean diameters, due to efficient fog-scavenging occurring almost every night, preventing particle growth (23). Nevertheless, the Org60 for the biomassburning OA (BBOA) and aqSOA factors behave consistently with what observed in Bologna2013, with the size distribution of the Org60 in aqSOA peaking at higher size (∼500-nm Dva) compared with the Org60 in BBOA (200-nm Dva). Biomass-Burning Emissions as Precursors of the aqSOA. In both datasets, we observe the presence of the guaiacol dimer (C14H14O4+), Gilardoni et al.
Table 1. O:C ratios of the aqSOA measured for SPC2011 and of the OA factors (including the aqSOA) for Bologna2013, together with literature values of laboratory aqSOA and cloud water samples OA type Fog water aqSOA event 1 aqSOA event 2 aqSOA event 3 aqSOA event 9 HOA BBOA OOA1 or aqSOA OOA2 OOA3 Low-volatility cloud water organics Gas-phase SOA Glyoxal aqSOA Phenols aqSOA Phenols aqSOA
O:C (AA) 0.53 (0.08) 0.61 (0.09) 0.61 (0.09) 0.61 (0.09) 0.62 (0.09) 0.08 (0.01) 0.26 (0.04) 0.57 (0.09) 0.44 (0.07) 0.66 (0.10) 0.52–0.59
O:C (AI) 0.68 0.83 0.84 0.83 0.82 0.10 0.33 0.81 0.56 0.83
(0.08) (0.10) (0.10) (0.10) (0.10) (0.01) (0.04) (0.10) (0.07) (0.10)
0.3–0.4 1–1.8 0.85–1.23 0.8–1.06
Site
Notes
SPC SPC SPC SPC SPC Bologna Bologna Bologna Bologna Bologna Whistler
Fall 2011 Fall 2011 Fall 2011 Fall 2011 Fall 2011 Winter 2013 Winter 2013 Winter 2013 Winter 2013 Winter 2013 Ambient Chamber Chamber Chamber Chamber
Source This study
This study
Lee et al. (20) Aiken et al. (57) Lee et al. (14) Yu et al. (13) Sun et al. (16)
detected by the HR-ToF-AMS at the exact mass 246.0887 (Fig. S4). The guaiacol dimer is a phenolic species directly emitted during lignin combustion, but it can also be formed in atmospheric liquid water through radical recombination of the guaiacol monomer (13, 16). Concentrations of other phenols and anhydrosugars measured by GC/MS (vanillin, vanillic acid, syringol, syringic acid, pyrogallol, and levoglucosan) that are typical tracers of wood combustion emissions (10) covary with the HR-ToF-AMS guaiacol dimer signal (Fig. S4). The guaiacol dimer signal during the Bologna2013 experiment (Fig. 2A) correlates well with BBOA for aqSOA < 0.3 μg·m−3 (r = 0.95, significant at P < 0.001), indicating a dominant contribution of primary sources for the measured guaiacol dimer during part of the experiment (i.e., when ALWC was low and aqSOA formation was not observed). However, we observe that, when aqSOA concentration increases, the dimer signal increases by 40% on average, indicating that aqSOA is also contributing to the observed guaiacol dimer concentration. In SPC2011 (Fig. 2B), the guaiacol dimer signal correlates well both with BBOA (r = 0.96, P < 0.001) and with aqSOA after fog dissipation (r = 0.96, P < 0.001), suggesting that primary and secondary sources of the dimer were comparable (note that only the data collected after fog dissipation are reported here, to isolate the effects of fog processing on aqSOA formation). We further stress the link between biomass burning and aqSOA using a schematic representation of biomass-burning aging based on specific mass spectrometry features previously used in literature (32, 33). Fresh biomass-burning emissions (BBOA) show a high content of anhydrosugars, like levoglucosan, which are characterized by the aforementioned signal at m/z 60 (C2H4O2+) (Figs. S5–S7). During atmospheric aging, the relative intensity of anhydrosugar signal decreases due to degradation and oxidation reactions. At the same time, atmospheric aging leads to the increase of oxygenated moieties, which translates into the increase of oxygenated fragments in the mass spectrum, the most intense of which is at m/z 44 (CO2+) (Figs. S5–S7). Fig. 2D shows that the spectral features of aqSOA are those typical of aged OA (large signal at m/z 44) but also indicate the presence of anhydrosugars (signal at m/z 60) above background levels, laying in the graph space that is typical of aged biomass-burning emissions. Overall, Gilardoni et al.
these results point to the fact that the observed aqSOA originate from the processing of biomass burning (BBOA) in both datasets. The evolution of the BBOA into aqSOA is further analyzed in Fig. 3 for both datasets. Fig. 3A shows the O:C and the hydrogento-carbon (H:C) values of the aqSOA and BBOA factors in the Van Krevelen (VK) diagram, which is typically used to investigate the OA evolution during field and laboratory experiments (34, 35). We plot the elemental ratios of the PMF factors to remove the effect of physical mixing between secondary and primary aerosols, allowing for a clearer and stronger interpretation of the results in the VK space. Aerosol aging has the overall effect of increasing O:C ratios. The “H:C vs. O:C” slope of zero in the VK plot is equivalent to the replacement of a hydrogen atom with a OH moiety, whereas a slope of −1 indicates the formation of carboxylic acid groups (34). The slope of the line that links BBOA to aqSOA for Bologna2013 is close to zero, whereas in SPC2011 the slope is about −0.5. The different slopes suggest that, during Bologna2013, where aerosol processing took place in aerosol water (i.e., wet aerosol), the increase in O:C ratio was mainly driven by oligomerization with hydroxyl group formation through dark chemistry (36). This is probably due to the fact that dark chemistry is favored in aerosol water compared with cloud and fog water, due to the higher concentration of solute, which reduces OH radical availability (8, 29). Conversely, the negative slope in SPC2011 indicates that oxidation through formation of carboxylic acid moieties was more important, in agreement with the dominant role of photochemical processes driven by OH radical in cloud and fog water (8). Fig. 3B shows the organic functional group composition of the aqSOA obtained from H-NMR spectra (Supporting Information, 4. Positive Matrix Factorization Analysis, 4.2. Factor Analysis of H-NMR Spectra, and Figs. S8 and S9). Compared with SPC2011, the aqSOA of Bologna2013 has a similar carbonyl and carboxylic group fraction (C=O), but a higher content of hydroxyl/ether groups (R–O–) and oxygen–carbon–oxygen moieties (–O–CH– O–), which are totally absent in SPC2011. In addition, the smaller contribution of C–H groups in the Bologna2013 aqSOA indicates a higher degree of molecular-chain ramification and functionalization. The H-NMR functional group analysis is therefore consistent with the hypothesis of higher relevance of PNAS | September 6, 2016 | vol. 113 | no. 36 | 10015
EARTH, ATMOSPHERIC, AND PLANETARY SCIENCES
The elemental ratios are estimated by the AMS organic mass spectra using the Aiken ambient (AA) (57), and the ambient improved (AI) (58) methods. Uncertainty is reported between brackets. The AA method is known to underestimate O:C, whereas the AI method reproduces the O:C ratio of complex organic mixture within 10%. However, because most of the literature studies use the AA method, we report the O:C ratios calculated using both the AA and the AI parameterizations.
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Fig. 2. Influence of biomass-burning emissions on aqSOA formation. (A and B) Scatter plots of the guaiacol dimer signal (C14H14O4) vs. the BBOA loadings (in micrograms per cubic meter) color-coded as a function of aqSOA concentration in Bologna2013 and SPC2011. For the Bologna2013 dataset, the two slopes correspond to high (>4 μg·m−3) and low (
Edited by Barbara J. Finlayson-Pitts, University of California, Irvine, CA, and approved July 11, 2016 (received for review February 9, 2016)
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particulate matter air quality secondary organic aerosol biomass burning aqueous processing
|
O
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rganic aerosol (OA) is a dominant component of atmospheric aerosol. Field observations indicate that processed, that is, secondary OA (SOA), dominates over primary OA worldwide (1–3). Bottom-up and top-down estimates confirm that SOA accounts for up to 76% of ambient OA (1, 4). However, the estimates of global SOA budget are still largely uncertain (1, 5). An increasing number of experimental and modeling studies point toward aqueous-phase chemistry as a significant missing pathway for SOA formation (6–8). To date, most studies have investigated the formation of aqueous SOA (aqSOA) from natural biogenic emissions (6–8). Nevertheless, anthropogenic emissions, such as wood burning for residential heating, can contribute to the formation of aqSOA, both in urban and rural areas. In fact, water-soluble organic species (WSOC) can account for more than 50% of wood-burning emissions (9–11). Monosaccharides, dicarboxylic acids, and phenols emitted during wood combustion can act as aqSOA precursors (12–15). A few studies investigated formation and properties of aqSOA from biomass combustion through laboratory photochemical oxidation of single compounds, such as levoglucosan and phenolic species (12, 13, 16–18). However, ambient observations of aqSOA formation in environments with high wood-burning emissions are very limited. Phenol oligomers, which are tracers of primary wood burning and aqueous-phase processing of wood-burning emissions, were observed in Fresno in Winter 2006, but concentration and properties of the related aqSOA were not reported (16). The influence of aqueous-phase chemistry for SOA formation was suggested again in Fresno in Winter 2010 (19), but the oxidation level [oxygen-to-carbon ratio (O:C)] of the Fresno SOA was lower than expected, compared with the O:C of aqSOA formed from oxidation of wood-burning emissions in laboratory experiments (12–14, 16, 20). www.pnas.org/cgi/doi/10.1073/pnas.1602212113
To identify, quantify, and characterize aqSOA from biomass burning under real ambient conditions, we investigated the OA properties of ambient aerosol and fog water samples collected in the Po Valley (northern Italy) during the cold season, when the region is characterized by temperature below 10 °C, high relative humidity, and significant emissions from wood combustion from residential heating (21). We showed the usefulness of molecular tracer detection by on-line measurement techniques to track the formation of ambient aqSOA. We also infer that oxidation of biomass-burning emissions in wet aerosol is taking place mainly through the formation of hydroxyl/ether groups and oligomerization reactions. Finally, we show that aqSOA originating from biomass-burning emissions are strong absorbers of UV and visible light, thereby contributing to a positive direct forcing. Discussion Ambient Observations of SOA Formed in the Aqueous Phase. The
observations discussed here were obtained during two different field experiments. The first study was performed at the rural site of San Pietro Capofiume (SPC), near Bologna, in Fall 2011, whereas the second experiment took place at an urban background site in Bologna during Winter 2013. The Fall 2011 campaign at SPC (SPC2011) was characterized by several fog episodes. The evaporation of fog left behind particles enriched in oxidized OA. To study the specific effect of fog dissipation on OA properties, we focused on four dissipation Significance Organic aerosol (OA) is a dominant component of atmospheric aerosol worldwide, and it is recognized as a key factor affecting air quality and possibly climate. Observations indicate that more than one-half of the global OA is of secondary origin. Traditional models typically underpredict secondary organic aerosol (SOA) mass, suggesting that a complete knowledge of SOA formation mechanisms is lacking. We show that aqueous-phase processing of biomass-burning emissions contributes to SOA formation. Such aqueous SOA absorbs UV and visible light more efficiently that other OA components. Aqueous chemistry processing of biomass-burning emissions should be taken into account in air quality and climate models for a correct description of the global OA budget and its climate-relevant optical properties. Author contributions: S.G., S.F., and M.C.F. designed research; S.G., M.P., L.G., C.C., M.R., S.D., S.S., M.C.P., M.V., and F.S. performed research; S.G., P.M., M.P., F.C., and G.P.G. analyzed data; and S.G., P.M., and M.P. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. Freely available online through the PNAS open access option. 1
To whom correspondence should be addressed. Email: [email protected].
2
Present address: Proambiente S.c.r.l., CNR Research Area, 40129 Bologna, Italy.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.1602212113/-/DCSupplemental.
PNAS | September 6, 2016 | vol. 113 | no. 36 | 10013–10018
EARTH, ATMOSPHERIC, AND PLANETARY SCIENCES
The mechanisms leading to the formation of secondary organic aerosol (SOA) are an important subject of ongoing research for both air quality and climate. Recent laboratory experiments suggest that reactions taking place in the atmospheric liquid phase represent a potentially significant source of SOA mass. Here, we report direct ambient observations of SOA mass formation from processing of biomass-burning emissions in the aqueous phase. Aqueous SOA (aqSOA) formation is observed both in fog water and in wet aerosol. The aqSOA from biomass burning contributes to the “brown” carbon (BrC) budget and exhibits light absorption wavelength dependence close to the upper bound of the values observed in laboratory experiments for fresh and processed biomass-burning emissions. We estimate that the aqSOA from residential wood combustion can account for up to 0.1–0.5 Tg of organic aerosol (OA) per y in Europe, equivalent to 4–20% of the total OA emissions. Our findings highlight the importance of aqSOA from anthropogenic emissions on air quality and climate.
10014 | www.pnas.org/cgi/doi/10.1073/pnas.1602212113
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events that were not perturbed by transport of air masses from surrounding areas (Supporting Information, 1. Identification of Radiative Fog Dissipation Events at San Pietro Capofiume During the 2011 Study and Table S1). The OA was analyzed by the Aerodyne (Aerodyne Research) high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) (22). The campaign results have been reported in a previous work (23). In this study, the SOA mass spectrum for each fog event is obtained as the total OA minus the primary OA, as determined by positive matrix factorization (PMF) analysis; the spectrum of fog water samples is instead measured via off-line analysis (see Methods for details). The SOA spectra after fog dissipation are very similar to the OA spectrum in fog water (Fig. S1), with a Pearson correlation coefficient (r) larger than 0.96 in all cases (and P < 0.001). This result indicates that the OA species observed in the aerosol particle phase after fog dissipation were originally present in fog water. The field experiment performed in Bologna in Winter 2013 (Bologna2013) was characterized by temperatures below 10 °C, high relative humidity, and stagnant air. Although dense fog events did not occur in the urban setting, the ambient relative humidity was typically above 70%, favoring the presence of wet aerosol particles. Similar to SPC2011, we applied PMF analysis (24) on the HR-ToF-AMS data collected in Bologna2013, to deconvolve the total OA signal in various components (Supporting Information, 4. Positive Matrix Factorization Analysis, 4.1. Positive Matrix Factorization of HR-TOF-AMS OA Data During Bologna 2013). Among the different OA types, we identified an oxygenated organic aerosol (OOA) component originating from biomass burning that has mass spectral features similar to the SOA observed in SPC2011 after fog dissipation (correlation with r = 0.94 and P < 0.001), therefore suggesting influence of aqueous-phase processing. From now on, we refer to these SOAs as aqSOAs. The spectra of the aqSOA for SPC2011 and Bologna2013 are shown together in Fig. 1A, and they show characteristic signals at m/z 29 (CHO+), m/z 43 (C2H3O+), m/z 44 (CO2+), and m/z 60 (C2H4O2+). In the following paragraphs, we report a series of findings to support our hypothesis that these SOAs are indeed aqSOAs. The first evidence of aqSOA formation is given by the correlation of these SOA samples with a tracer of liquid phase chemistry, that is, the hydroxymethanesulfonate (HMS). HMS is formed from the complexation of sulfite and bisulfite with aqueous formaldehyde (25–28). During both campaigns, HMS was detected by the HR-ToF-AMS and was also measured by proton NMR (H-NMR) (Methods and Supporting Information, 2. Tracers of Aqueous-Phase Chemistry and Fig. S2). For SPC2011, the aqSOA concentration increased together with the HMS signal after fog dissipation (r = 0.77, P < 0.001). Because photochemistry prevents HMS formation, the correlation of HMS with aqSOA could not be justified by radiation increase during the first hours after sunrise, when fog dissipates. Instead, the data indicate that HMS and aqSOA were formed in the same environment, that is, in the aqueous phase, consistent with previous literature (8, 29). Good correlation (r = 0.68, P < 0.001) is found between aqSOA and HMS signal for Bologna2013 as well. In addition, Fig. 1B shows that aqSOA in Bologna correlates well (r = 0.73, P < 0.001) with the aerosol liquid water content (ALWC) estimated from particle composition (Methods), confirming that the aqueous phase was the formation medium for this OA. Second, we consider the elemental composition of the aqSOA (Table 1). The O:C ratios observed for the aqSOA in this study are around 0.61–0.62 as calculated with the Aiken ambient (AA) method (Table 1). The corresponding ambient improved (AI) O:C ratios (0.81–0.84) are similar to the AI O:C ratio of aqSOA obtained from laboratory oxidation of phenolic compounds (13, 16). Enhanced O:C ratios (AA O:C > 0.52) have also been reported for laboratory-generated SOA from the photooxidation of organic precursors in the aqueous phase (14, 20). Moreover, higher-than-usual O:C of SOA observed in various environments
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Fig. 1. Evidence of aqSOA formation. (A) Comparison of aqSOA mass spectra in Bologna2013 and in SPC2011; the spectra are highly correlated (r = 94, P < 0.001). Notably, the mass spectrum of the SPC2011 aqSOA has a much larger CO2+ fraction than the spectrum of Bologna2013 aqSOA. (B) Scatter plot of aqSOA vs. the estimated aerosol liquid water content (ALWC) for Bologna2013 (upper and lower bounds). (C) Normalized size distribution of mass fragment m/z 60 (Org60) in BBOA-rich particles (i.e., samples with BBOA organic mass fraction larger than 70%) and in aqSOA-rich particles (i.e., samples with aqSOA organic mass fraction larger than 30%, and corrected for BBOA contribution).
at high relative humidity have been correctly modeled and explained solely by an aqueous-phase chemistry scheme (7). Last, we consider the particle size distribution of the aqSOA. Fig. 1C shows the size distribution of the mass fragment at m/z 60 (C2H4O2+; exact mass, 60.0206), or Org60, a marker for biomass burning (30) and a component of aqSOA mass spectrum. During the Bologna2013 campaign (Fig. 1C, Left), the size distribution of Org60 for the aqSOA factor shows a median mass diameter above 700-nm Dva, consistently with aqueous-phase reaction products (31). Additional particle time-of-flight (pToF) size distributions for other aerosol species during Bologna2013 are reported in Fig. S3. For SPC2011 (Fig. 1C, Right), the pToF size distributions of organic and inorganic chemical species are analyzed in a previous work (23). They are characterized by smaller mean diameters, due to efficient fog-scavenging occurring almost every night, preventing particle growth (23). Nevertheless, the Org60 for the biomassburning OA (BBOA) and aqSOA factors behave consistently with what observed in Bologna2013, with the size distribution of the Org60 in aqSOA peaking at higher size (∼500-nm Dva) compared with the Org60 in BBOA (200-nm Dva). Biomass-Burning Emissions as Precursors of the aqSOA. In both datasets, we observe the presence of the guaiacol dimer (C14H14O4+), Gilardoni et al.
Table 1. O:C ratios of the aqSOA measured for SPC2011 and of the OA factors (including the aqSOA) for Bologna2013, together with literature values of laboratory aqSOA and cloud water samples OA type Fog water aqSOA event 1 aqSOA event 2 aqSOA event 3 aqSOA event 9 HOA BBOA OOA1 or aqSOA OOA2 OOA3 Low-volatility cloud water organics Gas-phase SOA Glyoxal aqSOA Phenols aqSOA Phenols aqSOA
O:C (AA) 0.53 (0.08) 0.61 (0.09) 0.61 (0.09) 0.61 (0.09) 0.62 (0.09) 0.08 (0.01) 0.26 (0.04) 0.57 (0.09) 0.44 (0.07) 0.66 (0.10) 0.52–0.59
O:C (AI) 0.68 0.83 0.84 0.83 0.82 0.10 0.33 0.81 0.56 0.83
(0.08) (0.10) (0.10) (0.10) (0.10) (0.01) (0.04) (0.10) (0.07) (0.10)
0.3–0.4 1–1.8 0.85–1.23 0.8–1.06
Site
Notes
SPC SPC SPC SPC SPC Bologna Bologna Bologna Bologna Bologna Whistler
Fall 2011 Fall 2011 Fall 2011 Fall 2011 Fall 2011 Winter 2013 Winter 2013 Winter 2013 Winter 2013 Winter 2013 Ambient Chamber Chamber Chamber Chamber
Source This study
This study
Lee et al. (20) Aiken et al. (57) Lee et al. (14) Yu et al. (13) Sun et al. (16)
detected by the HR-ToF-AMS at the exact mass 246.0887 (Fig. S4). The guaiacol dimer is a phenolic species directly emitted during lignin combustion, but it can also be formed in atmospheric liquid water through radical recombination of the guaiacol monomer (13, 16). Concentrations of other phenols and anhydrosugars measured by GC/MS (vanillin, vanillic acid, syringol, syringic acid, pyrogallol, and levoglucosan) that are typical tracers of wood combustion emissions (10) covary with the HR-ToF-AMS guaiacol dimer signal (Fig. S4). The guaiacol dimer signal during the Bologna2013 experiment (Fig. 2A) correlates well with BBOA for aqSOA < 0.3 μg·m−3 (r = 0.95, significant at P < 0.001), indicating a dominant contribution of primary sources for the measured guaiacol dimer during part of the experiment (i.e., when ALWC was low and aqSOA formation was not observed). However, we observe that, when aqSOA concentration increases, the dimer signal increases by 40% on average, indicating that aqSOA is also contributing to the observed guaiacol dimer concentration. In SPC2011 (Fig. 2B), the guaiacol dimer signal correlates well both with BBOA (r = 0.96, P < 0.001) and with aqSOA after fog dissipation (r = 0.96, P < 0.001), suggesting that primary and secondary sources of the dimer were comparable (note that only the data collected after fog dissipation are reported here, to isolate the effects of fog processing on aqSOA formation). We further stress the link between biomass burning and aqSOA using a schematic representation of biomass-burning aging based on specific mass spectrometry features previously used in literature (32, 33). Fresh biomass-burning emissions (BBOA) show a high content of anhydrosugars, like levoglucosan, which are characterized by the aforementioned signal at m/z 60 (C2H4O2+) (Figs. S5–S7). During atmospheric aging, the relative intensity of anhydrosugar signal decreases due to degradation and oxidation reactions. At the same time, atmospheric aging leads to the increase of oxygenated moieties, which translates into the increase of oxygenated fragments in the mass spectrum, the most intense of which is at m/z 44 (CO2+) (Figs. S5–S7). Fig. 2D shows that the spectral features of aqSOA are those typical of aged OA (large signal at m/z 44) but also indicate the presence of anhydrosugars (signal at m/z 60) above background levels, laying in the graph space that is typical of aged biomass-burning emissions. Overall, Gilardoni et al.
these results point to the fact that the observed aqSOA originate from the processing of biomass burning (BBOA) in both datasets. The evolution of the BBOA into aqSOA is further analyzed in Fig. 3 for both datasets. Fig. 3A shows the O:C and the hydrogento-carbon (H:C) values of the aqSOA and BBOA factors in the Van Krevelen (VK) diagram, which is typically used to investigate the OA evolution during field and laboratory experiments (34, 35). We plot the elemental ratios of the PMF factors to remove the effect of physical mixing between secondary and primary aerosols, allowing for a clearer and stronger interpretation of the results in the VK space. Aerosol aging has the overall effect of increasing O:C ratios. The “H:C vs. O:C” slope of zero in the VK plot is equivalent to the replacement of a hydrogen atom with a OH moiety, whereas a slope of −1 indicates the formation of carboxylic acid groups (34). The slope of the line that links BBOA to aqSOA for Bologna2013 is close to zero, whereas in SPC2011 the slope is about −0.5. The different slopes suggest that, during Bologna2013, where aerosol processing took place in aerosol water (i.e., wet aerosol), the increase in O:C ratio was mainly driven by oligomerization with hydroxyl group formation through dark chemistry (36). This is probably due to the fact that dark chemistry is favored in aerosol water compared with cloud and fog water, due to the higher concentration of solute, which reduces OH radical availability (8, 29). Conversely, the negative slope in SPC2011 indicates that oxidation through formation of carboxylic acid moieties was more important, in agreement with the dominant role of photochemical processes driven by OH radical in cloud and fog water (8). Fig. 3B shows the organic functional group composition of the aqSOA obtained from H-NMR spectra (Supporting Information, 4. Positive Matrix Factorization Analysis, 4.2. Factor Analysis of H-NMR Spectra, and Figs. S8 and S9). Compared with SPC2011, the aqSOA of Bologna2013 has a similar carbonyl and carboxylic group fraction (C=O), but a higher content of hydroxyl/ether groups (R–O–) and oxygen–carbon–oxygen moieties (–O–CH– O–), which are totally absent in SPC2011. In addition, the smaller contribution of C–H groups in the Bologna2013 aqSOA indicates a higher degree of molecular-chain ramification and functionalization. The H-NMR functional group analysis is therefore consistent with the hypothesis of higher relevance of PNAS | September 6, 2016 | vol. 113 | no. 36 | 10015
EARTH, ATMOSPHERIC, AND PLANETARY SCIENCES
The elemental ratios are estimated by the AMS organic mass spectra using the Aiken ambient (AA) (57), and the ambient improved (AI) (58) methods. Uncertainty is reported between brackets. The AA method is known to underestimate O:C, whereas the AI method reproduces the O:C ratio of complex organic mixture within 10%. However, because most of the literature studies use the AA method, we report the O:C ratios calculated using both the AA and the AI parameterizations.
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Fig. 2. Influence of biomass-burning emissions on aqSOA formation. (A and B) Scatter plots of the guaiacol dimer signal (C14H14O4) vs. the BBOA loadings (in micrograms per cubic meter) color-coded as a function of aqSOA concentration in Bologna2013 and SPC2011. For the Bologna2013 dataset, the two slopes correspond to high (>4 μg·m−3) and low (
